"""simple docstring"""






import random
import unittest

import torch

from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin

@skip_mps
class lowerCamelCase		(__snake_case     ,     __snake_case     ,     unittest.TestCase   ):






					'''simple docstring'''


					a 						=		IFInpaintingSuperResolutionPipeline
					a 						=		TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {'width', 'height'}
					a 						=		TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS.union({"original_image"}   )
					a 						=		PipelineTesterMixin.required_optional_params - {'latents'}



					def       lowerCAmelCase_       (    self      :					int		)				->							Union[str, Any]:
									return self._get_superresolution_dummy_components()



					def       lowerCAmelCase_       (    self      :					Optional[int] ,			_snake_case      :					Optional[int] ,			_snake_case      :					List[Any]=0		)				->							Optional[Any]:






									if str(_snake_case		).startswith("mps"		):
													SCREAMING_SNAKE_CASE__			=					torch.manual_seed(_snake_case		)
									else:
													SCREAMING_SNAKE_CASE__			=					torch.Generator(device=_snake_case		).manual_seed(_snake_case		)

									SCREAMING_SNAKE_CASE__			=					floats_tensor((1, 3, 16, 16) ,			rng=random.Random(_snake_case		)		).to(_snake_case		)
									SCREAMING_SNAKE_CASE__			=					floats_tensor((1, 3, 32, 32) ,			rng=random.Random(_snake_case		)		).to(_snake_case		)
									SCREAMING_SNAKE_CASE__			=					floats_tensor((1, 3, 32, 32) ,			rng=random.Random(_snake_case		)		).to(_snake_case		)

									SCREAMING_SNAKE_CASE__			=					{
									    "prompt": "A painting of a squirrel eating a burger",
									    "image": image,
									    "original_image": original_image,
									    "mask_image": mask_image,
									    "generator": generator,
									    "num_inference_steps": 2,
									    "output_type": "numpy",
									}

									return inputs



					@unittest.skipIf(
					    torch_device != "cuda" or not is_xformers_available() ,			reason="XFormers attention is only available with CUDA and `xformers` installed" ,			)
					def       lowerCAmelCase_       (    self      :					Any		)				->							str:
									self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3		)



					def       lowerCAmelCase_       (    self      :					Optional[Any]		)				->							List[str]:
									self._test_save_load_optional_components()



					@unittest.skipIf(torch_device != "cuda" ,			reason="float16 requires CUDA"		)
					def       lowerCAmelCase_       (    self      :					Union[str, Any]		)				->							Optional[Any]:
									super().test_save_load_floataa(expected_max_diff=1e-1		)



					def       lowerCAmelCase_       (    self      :					Union[str, Any]		)				->							List[str]:
									self._test_attention_slicing_forward_pass(expected_max_diff=1e-2		)



					def       lowerCAmelCase_       (    self      :					Tuple		)				->							Tuple:
									self._test_save_load_local()



					def       lowerCAmelCase_       (    self      :					Optional[int]		)				->							List[str]:
									self._test_inference_batch_single_identical(
									    expected_max_diff=1e-2 ,			)








"""simple docstring"""



from collections import Counter
from timeit import timeit
def      UpperCAmelCase     (       _lowercase :   str = ""			,   )						-> bool:


	"""simple docstring"""




	return sum(c % 2 for c in Counter(input_str.replace(''' '''			,   ''''''	).lower()	).values()	) < 2
def      UpperCAmelCase     (       _lowercase :   str = ""	)						-> bool:


	"""simple docstring"""




	if len(_lowercase	) == 0:
		return True
	lowerCAmelCase_      							=			input_str.replace(''' '''			,   ''''''	).lower()
	# character_freq_dict: Stores the frequency of every character in the input string
	lowerCAmelCase_      							=			{}

	for character in lower_case_input_str:
		lowerCAmelCase_      							=			character_freq_dict.get(_lowercase			,   0	) + 1
	lowerCAmelCase_      							=			0

	for character_count in character_freq_dict.values():
		if character_count % 2:
			odd_char += 1
	if odd_char > 1:
		return False
	return True
def      UpperCAmelCase     (       _lowercase :   str = ""	)						-> None:


	"""simple docstring"""




	print('''\nFor string = '''			,   _lowercase			,   ''':'''	)
	print(
	    '''> can_string_be_rearranged_as_palindrome_counter()'''			,   '''\tans ='''			,   can_string_be_rearranged_as_palindrome_counter(_lowercase	)			,   '''\ttime ='''			,   timeit(
	        '''z.can_string_be_rearranged_as_palindrome_counter(z.check_str)'''			,   setup='''import __main__ as z'''			,   )			,   '''seconds'''			,   )
	print(
	    '''> can_string_be_rearranged_as_palindrome()'''			,   '''\tans ='''			,   can_string_be_rearranged_as_palindrome(_lowercase	)			,   '''\ttime ='''			,   timeit(
	        '''z.can_string_be_rearranged_as_palindrome(z.check_str)'''			,   setup='''import __main__ as z'''			,   )			,   '''seconds'''			,   )


if __name__ == "__main__":
		lowercase_							=							input(
		    'Enter string to determine if it can be rearranged as a palindrome or not: '
		).strip()
		benchmark(check_str)
		lowercase_							=							can_string_be_rearranged_as_palindrome_counter(check_str)
		print(f"""{check_str} can {'' if status else 'not '}be rearranged as a palindrome""")